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docs: Update mlir.md

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Jeremy Bradley-Silverio Donato
2022-01-06 17:37:18 +01:00
committed by Benoit Chevallier
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docs/dev/explanation/mlir.md
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@@ -17,7 +17,7 @@ The conversion uses as input the operation graph to convert, as well as a dictio
## Define function signature
The first step would be to define the function signature (excluding return value at this point). We will convert input node's types to MLIR (e.g. convert `EncryptedTensor(Integer(64, is_signed=False), shape=(4,))` to `tensor<4xi64>`) and map their values to the argument of the function. So if we had an operation graph with one `EncryptedScalar(Integer(7, is_signed=False))`, we will get an MLIR function like `func @main(%arg0 : !FHE.eint<7>) -> (<ret-type>)`. Note that the return type would be detected automatically later on when returning MLIR values.
The first step is to define the function signature (excluding return value at this point). We will convert the input node's types to MLIR (e.g. convert `EncryptedTensor(Integer(64, is_signed=False), shape=(4,))` to `tensor<4xi64>`) and map their values to the argument of the function. So if we had an operation graph with one `EncryptedScalar(Integer(7, is_signed=False))`, we will get an MLIR function like `func @main(%arg0 : !FHE.eint<7>) -> (<ret-type>)`. Note that the return type would be detected automatically later on when returning MLIR values.
## Convert nodes in the OpGraph